Of course we’re aware that a study not conducted by a third party can lead to bias. While it’s clear that the accuracy of Google Translate is much better than both Amazon and Microsoft, DeepL seems to lead in the above language pairs. How do these providers actually perform when it comes to some of the most common language pairs? We found a study done by DeepL looking at the following language pairs: Research from Intento shows that Google and DeepL rank highest (out of 18 generic engines) for more or less all language pairs, with Google taking the lead: DeepL is currently available in 29 languages, while GT is available in over 130. Because GT supports so many languages, its accuracy depends on the specific language pairs you’re targeting.įor example, translating from English to Spanish has a very high accuracy rate (94%) because it’s such a common language pair. In contrast, translating from English to Armenian has a lower accuracy rate (55%) because it’s not nearly as popular.ĭeepL and Google Translate are the most popular generic machine translation (MT) engines on the market. Here are the Google Translate accuracy numbers for the following target languages using English source content:Īs you can see, there’s a wide accuracy range for different target languages. In a study carried out in part by the UCLA Medical Center, they found that “overall, Google Translate accurately conveyed the meaning of 330/400 (82.5%) instructions examined but the accuracy varied by language from 55 to 94%.” So how accurately does GT translate content? You want to know how it can work for you. Here’s everything you need to know about GT, and when it’s worth considering for your business. Even if machine translation isn’t yet perfect, it can already help humans translate much faster.
Between the media hype and exaggerated claims, sometimes it’s hard to distinguish when machine translation will actually be good enough for most use cases.īut in the past five years, we’ve seen neural machine translation engines like Google Translate (GT) really take off.
In just one year, Subway saw an over 1,000% return on their investment. Savings based on four languages: $172,372 (or 44%) and at least 2 months of time. When the idea to use machine translation for Subway’s content surfaced, their Globalization Services Manager, Carrie Fischer, said: “There’s no way this is going to work for Subway’s content.”Ī little later, she chose to give it a go.
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